Analyze architecture for consistency between ADRs and AD, completeness, and quality issues. Use when validating generated or refined architecture artifacts, before feature development, during architecture review, or periodically to detect drift.
Refine and validate system-level ADRs through targeted clarification questions. Use when ADRs need review, gaps need filling, or ADR status must be approved before architecture generation.
Generate a full Architecture Description (AD.md) from accepted ADRs using multi-agent DAG orchestration. Use when accepted ADRs exist and you need to produce or update unified architecture documentation.
Reverse-engineer architecture from an existing codebase to create ADRs documenting discovered decisions. Use when bootstrapping architecture documentation for brownfield projects.
Interactive PRD exploration and system-level ADR creation for greenfield projects. Use when transforming a PRD or high-level system description into Architecture Decision Records.
Review, accept, reject, or defer Change Decision Records (ChDRs) discovered by change-init. Interactive one-ChDR-at-a-time workflow that validates inferred decisions against their git/issue evidence before promotion to project memory.
Mine git history for Change Decision Records (ChDRs) by detecting commit messages that link to issue trackers, clustering the commits into change stories, and inferring the decisions behind them. Use when bootstrapping project memory from an existing repo's history (brownfield), before refactoring unfamiliar code, or…
Promote accepted Change Decision Records (ChDRs) from drafts to project memory at .adlc/memory/chdr/, write OKF-style frontmatter, and regenerate the boot-facing .adlc/memory/chdr.md index that team-boot injects at session start. Use after /change-clarify has accepted ChDRs.
Analyze evaluation results and close the loop. Specification failures create local CDRs to fix agent rules; generalization failures go to evaluator backlog.
Initialize evals/{system}/ directory structure for evaluation system following EDD principles (Standalone). Choose PromptFoo or DeepEval based on tech stack, generate security baseline.
Review, accept, reject, or defer Context Directive Records (CDRs) discovered by levelup-init or proposed by levelup-specify. Interactive one-CDR-at-a-time workflow.
Reverse-engineer Context Directive Records (CDRs) from an existing codebase for contribution to team-ai-directives. Use when bootstrapping team knowledge from brownfield projects.
Compile accepted Context Directive Records (CDRs) into team-ai-directives artifacts and create a draft PR. Builds context modules, evals goldensets, and/or skills based on CDR context types.
Extract Context Directive Records (CDRs) from the current session after completing work. Identifies reusable patterns (rules, personas, examples, evals) and captures directive compliance cases for team-ai-directives.
Mission-driven SDD orchestrator: take a feature description, structure it into a Mission Brief (goal, constraints, success criteria), generate an ordered step list with prompts that trigger installed SDD skills via model invocation or command-file discovery, and walk those steps to converged implementation. Use when…
Read-only analysis of PDR↔PRD consistency, PDR quality, cross-PDR conflicts, and staleness. Outputs a structured markdown report with severity-assigned findings. Use after /product-implement or periodically to detect drift.
Refine and validate Product Decision Records through targeted clarification questions. Review PDR completeness, detect conflicts, approve decisions, and update status to Accepted. Use before /product-implement.
Generate a full Product Requirements Document (PRD.md) from accepted PDRs using multi-agent DAG orchestration. Reads individual PDR files, generates PRD sections from templates, validates output, and promotes accepted PDRs to memory. Use after /product-clarify.
Reverse-engineer Product Decision Records (PDRs) from an existing codebase and documentation using multi-agent feature-area analysis (brownfield). Use when documenting product decisions inferred from an already-built product.
Track milestone progress across four layers of truth — decision state (PDR status), execution state (live issue tracker via MCP), evidence state (code-vs-PDR verification), and gate state (milestone gates). Shows honest completion, done-means warnings, and updates status only when all layers are green. Use for weekly…